Pathology

Leveraging TME features and multi-omics data with an advanced deep learning framework for improved Cancer survival prediction.

Glioma, a malignant intracranial tumor with high invasiveness and heterogeneity, significantly impacts patient survival. This study integrates multi-omics data to improve prognostic prediction and identify therapeutic targets. Using single-cell data from glioblastoma (GBM) and low-grade glioma (LGG) samples, we identified 55 distinct cell states via the EcoTyper framework, validated for stability ...

Exploring hypoxia driven subtypes of pulmonary arterial hypertension through transcriptomics single cell sequencing and machine learning.

Pulmonary arterial hypertension (PAH) is a progressive cardiovascular disease characterized by elevated pulmonary arterial pressure, leading to right heart failure and death. Despite advancements in diagnosis and treatment, it remains incurable, and its mechanisms are poorly understood. This study aimed to integrate multi-omics data analysis and machine learning techniques to uncover the molecular...

Pruning Sparse Tensor Neural Networks Enables Deep Learning for 3D Ultrasound Localization Microscopy.

Ultrasound Localization Microscopy (ULM) is a non-invasive technique that allows for the imaging of micro-vessels in vivo, at depth and with a resolut...

Development of a Low-Profile, Piezoelectric Robot for MR-Guided Abdominal Needle Interventions.

PURPOSE: Minimally invasive needle-based interventions are commonly used in cancer diagnosis and treatment, including procedures, such as biopsy, brac...

Impact of CT reconstruction algorithms on pericoronary and epicardial adipose tissue attenuation.

OBJECTIVE: This study aims to investigate the impact of adaptive statistical iterative reconstruction-Veo (ASIR-V) and deep learning image reconstruct...

Single Molecule Localization Super-resolution Dataset for Deep Learning with Paired Low-resolution Images.

Deep learning super-resolution microscopy has advanced rapidly in recent years. Super-resolution images acquired by single molecule localization micro...

Host Biomarkers and Antibiotic Tissue Penetration in Sepsis: Insights from Moxifloxacin.

BACKGROUND AND OBJECTIVE: Sepsis-induced pathophysiological changes may lead to pharmacokinetic variability which alters antibiotic concentrations at ...

AI-based phenotyping of hepatic fiber morphology to inform molecular alterations in metabolic dysfunction-associated steatotic liver disease.

BACKGROUND AND AIMS: Hepatic fiber morphology may significantly enhance our understanding of molecular alterations in metabolic dysfunction-associated...

The association of trimethylamine N-oxide with diabetic retinopathy Pathology: Insights from network toxicology and molecular docking analysis.

Trimethylamine N-oxide (TMAO), a gut microbiota-derived metabolite, has emerged as a potential contributor to diabetic retinopathy (DR) progression. H...

A comprehensive image dataset for accurate diagnosis of betel leaf diseases using artificial intelligence in plant pathology.

In South Asian countries, agriculture is a crucial employment field, and a remarkable number of people depend on it for their livelihood. Crop disease...

Deep learning-aided segmentation combined with finite element analysis reveals a more natural biomechanic of dinosaur fossil.

Finite element analysis (FEA), a biomechanical simulation technique capable of providing direct mechanical visualization for CT-based digital models, ...

Deep learning for automated segmentation of brain edema in meningioma after radiosurgery.

BACKGROUND: Although gamma Knife radiosurgery (GKRS) is commonly used to treat benign brain tumors, such as meningioma, irradiating the surrounding br...

Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging.

Resolving arterial flows is essential for understanding cardiovascular pathologies, improving diagnosis, and monitoring patient condition. Ultrasound ...

Tissue Clutter Filtering Methods in Ultrasound Localization Microscopy Based on Complex-Valued Networks and Knowledge Distillation.

Ultrasound localization microscopy (ULM) is a blood flow imaging technique that utilizes micrometer-sized microbubbles (MBs) as contrast agents to ach...

Combining Ultrasound Imaging and Molecular Testing in a Multimodal Deep Learning Model for Risk Stratification of Indeterminate Thyroid Nodules.

Indeterminate cytology (Bethesda III and IV) represents 15-30% of biopsied thyroid nodules and require additional diagnostic testing. Molecular testi...

Bioinformatics Approach to Identifying Molecular Targets of Isoliquiritigenin Affecting Chronic Obstructive Pulmonary Disease: A Machine Learning Pharmacology Study.

To identify the molecular targets and possible mechanisms of isoliquiritigenin (ISO) in affecting chronic obstructive pulmonary disease (COPD) by regu...

Investigating handheld near-infrared spectroscopy for forensic body fluid analysis.

Forensic casework and crime scene examination will often involve the identification and analysis of biological evidence found on a wide variety of sur...

Efficient hybrid heuristic adopted deep learning framework for diagnosing breast cancer using thermography images.

The most dangerous form of cancer is breast cancer. This disease is life-threatening because of its aggressive nature and high death rates. Therefore,...

Comprehensive evaluation and application of tissue clearing techniques for 3-D visualization of splenic neural and immune architecture.

As the largest secondary lymphoid organ, the spleen plays a crucial role in initiating and sustaining immune responses against blood-borne pathogens t...

Machine learning prediction of HER2-low expression in breast cancers based on hematoxylin-eosin-stained slides.

BACKGROUND: Treatment with HER2-targeted therapies is recommended for HER2-positive breast cancer patients with HER2 gene amplification or protein ove...